Swarm is an educational framework for multi-agent orchestration that explores lightweight and ergonomic approaches to coordinating multiple AI agents.
The framework addresses the challenge of building systems where multiple agents need to work together, communicate, and hand off tasks to one another. Rather than imposing rigid architectural patterns, Swarm prioritizes simplicity and ease of use, allowing developers to define agent behaviors and transitions between agents in a straightforward manner. The approach centers on making agent coordination intuitive enough that developers can focus on business logic rather than orchestration complexity.
Swarm is designed primarily for developers exploring multi-agent patterns and those building applications that benefit from agent specialization and handoff workflows. It suits projects where you want to experiment with agent-based architectures without heavyweight frameworks or extensive boilerplate. The framework is positioned as educational, meaning it is intended to help developers understand multi-agent concepts and patterns rather than as a production-hardened system for large-scale deployments.
The project shows active development with regular updates and refinements to its core APIs. The codebase receives consistent attention to improving the developer experience, with changes focused on clarifying interfaces and expanding examples that demonstrate common multi-agent patterns. Documentation and example code are maintained alongside the core framework to support learning and adoption.
